Agent-Based Simulation of a Perpetual Futures Market
Ramshreyas Rao

TL;DR
This paper presents an agent-based model of Perpetual Futures markets that successfully reproduces the key feature of price pegging to the underlying spot market, allowing analysis of market microstructure and trader behaviors.
Contribution
It extends existing limit order book models to the complex environment of Perp markets, demonstrating how market and agent parameters influence trading premiums and behaviors.
Findings
The model reproduces the price peg of Perps to the Spot market.
Market parameters like order lifetime and spread affect trading premiums.
Biasing traders' behaviors aligns with empirical observations in real Perp markets.
Abstract
I introduce an agent-based model of a Perpetual Futures market with heterogeneous agents trading via a central limit order book. Perpetual Futures (henceforth Perps) are financial derivatives introduced by the economist Robert Shiller, designed to peg their price to that of the underlying Spot market. This paper extends the limit order book model of Chiarella et al. (2002) by taking their agent and orderbook parameters, designed for a simple stock exchange, and applying it to the more complex environment of a Perp market with long and short traders who exhibit both positional and basis-trading behaviors. I find that despite the simplicity of the agent behavior, the simulation is able to reproduce the most salient feature of a Perp market, the pegging of the Perp price to the underlying Spot price. In contrast to fundamental simulations of stock markets which aim to reproduce empirically…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComplex Systems and Time Series Analysis · Economic theories and models · Financial Markets and Investment Strategies
MethodsFocus
